ArticleBiomedical optics express2019
Automatic longitudinal montaging of adaptive optics retinal images using constellation matching.
Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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The trial behind it
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Who cites it
25 citing papers in PubMed.
- Multi-orientation non-confocal retinal imaging in an AOSLO using a Dove prism.Biomedical optics express · 2026Article
- Axicons for improved resolution and depth of focus in adaptive optics scanning light ophthalmoscopy.Biomedical optics express · 2025Article
- The Cone Optoretinogram as a Function of Retinal Eccentricity.Photonics · 2025Article
- The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems.Sensors (Basel, Switzerland) · 2025Article
- High refresh rate display for natural monocular viewing in AOSLO psychophysics experiments.Optics express · 2024Article
- Modeling Human Macular Cone Photoreceptor Spatial Distribution.Investigative ophthalmology & visual science · 2024Article
- Intervisit Reproducibility of Foveal Cone Density Metrics.Translational vision science & technology · 2024Article
- Normalized weighted cross correlation for multi-channel image registration.Optics continuum · 2024Article
- Automatic montaging of adaptive optics SLO retinal images based on graph theory.Biomedical optics express · 2024Article
- Substrip-based registration and automatic montaging of adaptive optics retinal images.Biomedical optics express · 2024Article
- Intensity-based optoretinography reveals sub-clinical deficits in cone function in retinitis pigmentosa.Frontiers in ophthalmology · 2024Article
- The effect of sampling window size on topographical maps of foveal cone density.Frontiers in ophthalmology · 2024Article
- Change in Cone Structure Over 24 Months in USH2A-Related Retinal Degeneration.American journal of ophthalmology · 2023Article
- Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects.Biomedical optics express · 2023Article
- Extracting spacing-derived estimates of rod density in healthy retinae.Biomedical optics express · 2023Article
- Repeatability and reciprocity of the cone optoretinogram.Biomedical optics express · 2022Article
- Automated Assessment of Photoreceptor Visibility in Adaptive Optics Split-Detection Images Using Edge Detection.Translational vision science & technology · 2022Article
- Short-term Assessment of Subfoveal Injection of Adeno-Associated Virus-Mediated hCHM Gene Augmentation in Choroideremia Using Adaptive Optics Ophthalmoscopy.JAMA ophthalmology · 2022Article
- Cone photoreceptor reflectance variation in the northern tree shrew and thirteen-lined ground squirrel.Experimental biology and medicine (Maywood, N.J.) · 2021Article
- Theoretical versus empirical measures of retinal magnification for scaling AOSLO images.Journal of the Optical Society of America. A, Optics, image science, and vision · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Adaptive optics (AO) scanning laser ophthalmoscopy offers a non-invasive approach for observing the retina at a cellular level. Its high resolution capabilities have direct application for monitoring and treating retinal diseases by providing quantitative assessment of cone health and density across time. However, accurate longitudinal analysis of AO images requires that AO images from different sessions be aligned, such that cell-to-cell correspondences can be established between timepoints. Such alignment is currently done manually, a time intensive task that is restrictive for large longitudinal AO studies. Automated longitudinal montaging for AO images remains a challenge because the intensity pattern of imaged cone mosaics can vary significantly, even across short timespans. This limitation prevents existing intensity-based montaging approaches from being accurately applied to longitudinal AO images. In the present work, we address this problem by presenting a constellation-based method for performing longitudinal alignment of AO images. Rather than matching intensity similarities between images, our approach finds structural patterns in the cone mosaics and leverages these to calculate the correct alignment. These structural patterns are robust to intensity variations, allowing us to make accurate longitudinal alignments. We validate our algorithm using 8 longitudinal AO datasets, each with two timepoints separated 6-12 months apart. Our results show that the proposed method can produce longitudinal AO montages with cell-to-cell correspondences across the full extent of the montage. Quantitative assessment of the alignment accuracy shows that the algorithm is able to find longitudinal alignments whose accuracy is on par with manual alignments performed by a trained rater.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.